Hairiness is an important quality parameter of spun yarns. It not only affects the quality of
yarns, but also the weaving and knitting performance of yarns as well as the quality of the …

Now in its fifth edition, John C. Russ's monumental image processing reference is an even
more complete, modern, and hands-on tool than ever before. The Image Processing …

During spinning, knitting and weaving processes, the yarn apparent evenness is an
important factor, which determines the quality of subsequent spinning production and fabric …

Yarn hairiness affects yarn and fabric quality. The existing hairiness detection methods
cannot discriminate crossover fibers or hairs. In order to accurately separate and detect …

Yarn hairiness is one of the key parameters influencing fabric quality. In this paper image
processing and analysis algorithms developed for an automatic determination of yarn …

To solve the problems of high labor intensity, low efficiency, and frequent errors in the
manual identification of cone yarn types, in this study five kinds of cone yarn were taken as …

Textile and clothing industry is one of the classical manufacturing industries which have
recently undergone major transformations due to delocalization and high market volatility. In …

The aim of this paper is the development of a new technological solution, for the automatic
characterization of the yarn mass parameters (linear mass, diameter, and hairiness) based …

In order to detect the length and root number of yarn hairiness more accurately, based on
the combination with video microscope and image processing technology, a novel hairiness …

For improving the efficiency, flexibility and robustness of yarn defect system, a new method
is proposed to evaluate the quality of yarn by testing the yarn diameter, defects and …